Table 6

Taxonomy of Fitted Multilevel Models for Change in Which Intern Post-conventional P Score is Modeled as a Function of Semester in Internship, Gender, and Verbal GRE Score (n of participants = 82; n of waves of longitudinal data = 3)

ParameterModel AModel BModel CModel D
Fixed Effects:      
InitialInterceptγ0041.95***37.03***41.95***33.53***
Status  (1.76)(1.76)(1.68)(3.39)
 FAMALEγ01 6.21 10.64**
    (4.26) (3.49)
 GREVγ02  0.07**0.07***
     (0.02)(0.01)
Rate ofInterceptγ10–0.16–1.14–0.14–0.18
change  (0.64)(1.41)(0.64)(0.64)
 FEMALEγ11 1.24  
    (1.58)  
 GREVγ12  -0.01 
     (0.01) 
Variance Components:      
Level-1:Within-personσ2ε64.70***64.42***64.03***64.64***
   (7.25)(7.25)(7.18)(7.24)
Level-2:In initial statusσ20199.38***190.68***176.70***158.18***
   (34.67)(33.30)(31.08)(28.36)
Goodness of fit:      
–2LL  1,877.81,873.51,867.21,861.3

Note: FEMALE = 1 for females and 0 for males. Verbal GRE score (GREV) is centered on its sample average. The model was estimated using full ML, SAS PROC MIXED.

~p <.1.

*p<.05.

**p<. 01.

***p<.001.

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